Vibration Measurement With Video Processing Based on Alternating Optimization of Frequency and Phase Shifts

• Published in: IEEE transactions on instrumentation and measurement Vol. 70; pp. 1 - 13
• Main Authors: Zhou, Jiwen, Li, Hongguang, Zhang, Li, Wang, Xiaojian, Li, Yun
• Format: Journal Article
• Language: English
• Published: New York IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Angular spatial frequency estimation; Digital imaging; Filter banks; Filtering; Frequency measurement; Image contrast; Image processing; Iterative algorithms; Iterative methods; Measurement methods; Measurement techniques; monocular vision; motion magnification; Optical flow; Optimization; Phase measurement; phase shifts; Phase unwrapping; Pixels; Regularization; Speckle patterns; Vibration; Vibration measurement; Vibrations; Video; Vision
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2021.3116322

Vision-based measurement methods have attracted growing interest over the past years because of their non-contact sensing capability for acquiring the full-field vibrations of structure. Existing vision-based measurement techniques, such as point tracking (PT) and digital image correlation (DIC), require preparation for the surface with high-contrast markers or speckle patterns before measurement. The phase-based motion magnification, enabling to extract the vibration of the structure without surface pre-processing, is a newly developed vision-based measurement method. However, it suffers from the problems, such as phase noise, phase instability, and phase unwrapping. In this article, a novel iterative algorithm called alternating optimization of frequency and phase shifts (AOFPS) is developed to measure the vibration signals from the video instead of explicitly manipulating the phase. The method of Tikhonov regularization for estimating pixel-to-pixel sinusoid patterns and the approach of the least squares for extracting frame-to-frame random phase shifts are alternately implemented to track the motion of the object. This algorithm provides robust and accurate vibration measurements without expensive computation. Simulated and laboratory experiments analyses illustrate the effectiveness and accuracy of the proposed algorithm.